JP6810673B2 - Equipment and programs for positioning - Google Patents

Description

The present disclosure relates to devices and programs for positioning.

Various services have been developed that utilize the position information obtained by positioning the user's position using the radio field intensity value of the beacon or WiFi (registered trademark), and the importance of the position information is increasing. As a method of positioning the user's position, in indoors where GPS (Global Positioning System) radio waves do not reach, positioning using an electric field map showing the strength of radio waves called a fingerprint using radio waves of multiple positioning beacons. There is a way.

As a method of constructing an electric field map used in the above positioning method, for example, in Non-Patent Document 1, an electric field map is constructed from training data outdoors in consideration of the influence of obstacles such as buildings and walls such as blocking and reflection. The method of doing so is disclosed.

"Construction of radio wave map considering obstacles in wireless radio positioning method", Masaaki Kuwahara, Nobuhiko Nishio, Multimedia, Distributed, Cooperative and Mobile (DICOMO2008) Symposium, July 2008

By the way, in constructing an electric field map, a radio wave propagation model is used, which represents the attenuation of radio waves according to the distance from a source such as a beacon that emits radio waves. If this radio wave propagation model is inappropriate, the strength of radio waves cannot be estimated accurately. For example, in the method of Non-Patent Document 1, there is a problem that the intensity of radio waves cannot be estimated accurately as the distance from the source of radio waves approaches.

The present disclosure has been made in consideration of the above problems, and provides an apparatus and a program for positioning capable of accurately estimating the intensity of radio waves regardless of the distance from the source of radio waves. With the goal.

In order to achieve the above object, the device for positioning in the first aspect of the present disclosure is a device for positioning that estimates the radio wave intensity at a desired position of the radio wave transmitted from the radio wave transmitting device. In the section corresponding to the distance from the radio wave transmitting device, the first section in which the rate of change of the radio wave intensity value with respect to the change in the distance is less than the threshold, and the section in which the rate of change of the radio wave intensity value is equal to or more than the threshold, the first The section is divided into a second section closer to the radio wave transmitting device than the section 1, and the second section is further divided into a plurality of sections. For each divided section, the closer the section is to the radio wave transmitting device, the higher the value. The radio wave propagation model expressed by one equation based on the distance between the radio wave transmitting device and the estimation target point for estimating the radio wave intensity by switching the value of the increasing space propagation coefficient and the space propagation coefficient is used. It is equipped with an electric field estimation unit that estimates the radio field intensity at the estimation target point.

The device for positioning in the second aspect of the present disclosure is the device for positioning in the first aspect, in which the radio field intensity of the estimated target point estimated by the electric field estimation unit and the radio field strength of the estimated target point are Further, a positioning unit that performs positioning of the estimation target point based on the actually measured value of the above is provided.

The third aspect of the present disclosure is the device for positioning in the first aspect or the second aspect, in which the second section is divided into shorter sections as it is closer to the radio wave transmitting device.

A fourth aspect of the present disclosure is a device for positioning in any one of the first to third aspects, wherein the radio wave propagation model outputs a maximum radio wave output of a radio wave transmitted by the radio wave transmitting device. When K, the distance between the radio wave transmitting device and the estimated target point is d, and the spatial propagation coefficient is n, the right side of the following equation (1) for deriving the RSSI (Received Signal Strength Indicator), which is the radio wave strength value, is used. At least expressed by the including expression,
RSSI = Kn × log ₁₀ d ... (1).

A fifth aspect of the present disclosure is the device for positioning in any one of the first to fourth aspects, wherein the intensity of the radio wave of the radio wave transmitting device is actually measured at each of the actually measured points whose positions are known. An optimization unit for optimizing the radio wave propagation model by optimizing the spatial propagation coefficient using the measured values obtained is further provided.

A sixth aspect of the present disclosure is the apparatus for positioning in the fifth aspect, wherein the optimization unit propagates the radio wave with respect to the measured value of the radio wave intensity with respect to at least two or more actual measurement points where the radio wave intensity is actually measured. The radio wave propagation is performed by deriving the spatial propagation coefficient related to the distance between the measured point and the radio wave transmitting device so as to minimize the optimization function representing the sum of the differences from the radio wave intensity value derived from the model. Optimize the model.

A seventh aspect of the present disclosure is the device for positioning in the sixth aspect, in which the optimization unit further weights the radio wave transmitting device and the measured point as the distance between them becomes closer, and the radio wave propagates. Optimize the model.

In order to achieve the above object, the program of the eighth aspect of the present disclosure causes the computer to function as each part of the device for positioning according to any one of the first to seventh aspects. belongs to.

According to the present disclosure, it is possible to accurately estimate the intensity of radio waves regardless of the distance from the source of radio waves.

It is a graph which shows an example of the radio wave propagation model in an embodiment. It is a graph for demonstrating an example of a radio wave propagation model in an embodiment. It is a figure for demonstrating an example of derivation of the actual electric field map in an embodiment. It is a block diagram which shows an example of the structure of the radio wave intensity estimation device in embodiment. It is a flowchart which shows an example of the radio wave propagation model derivation routine executed by the electric field estimation part in an embodiment. It is a flowchart which shows an example of the electric field map derivation routine executed by the radio field intensity estimation apparatus in embodiment. It is a figure which shows an example of the display of the actual electric field map derived by the radio wave intensity estimation apparatus in embodiment. It is a figure which shows another example of the display of the actual electric field map derived by the radio field intensity estimation apparatus in embodiment. It is a figure which shows an example of the display of the theoretical electric field map derived by the radio field intensity estimation apparatus in embodiment. It is a block diagram which shows an example of the structure of the apparatus for positioning in an embodiment. It is a block diagram which shows the implementation example of the radio wave intensity estimation apparatus in embodiment. It is a graph for demonstrating the approximation of the radio wave intensity value by a radio wave propagation model.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. The present embodiment does not limit the present invention. In the following, as an example, a case where the radio wave transmitting device is a beacon (Beacon) that transmits a beacon signal including a beacon ID (Identification) for identifying the own device will be described, but the radio wave transmitting device is limited to the beacon. It's not a thing. As such a beacon signal, for example, a WiFi (registered trademark) signal, a BLE (Bluetooth (registered trademark) Low Energy) signal, or the like can be used.

First, the radio wave propagation model of the present disclosure will be described.

Generally, the radio wave strength (RSSI: Received Signal Strength Indicator) of a beacon signal at a point away from the beacon is represented by a radio wave propagation model represented by the following equation (1). In the following equation (1), "d" is the distance (d> 0) from the beacon installation position, "K" is the maximum radio wave output of the beacon, and "n" is the spatial propagation coefficient. "C" is a constant term.

RSSI = K- (n x log ₁₀ d-C) ... (1)

The above-mentioned "K" is a known value, and "n" and "C" are model coefficients that change depending on the environment. The combination of n and C that best fits the plot of the measured points can be derived by various methods such as the least squares method. A radio wave propagation curve obtained by connecting the measured values of radio field intensity (hereinafter, may be simply referred to as "measured values") in the radio wave propagation model of the above equation (1) defined by the derived model coefficients (n, C). By approximating, it is possible to derive the radio field intensity at various points other than the measured points.

FIG. 12 shows a graph showing the relationship between the distance from the beacon and the radio field intensity. FIG. 12 shows an example of a graph of measured radio field intensities at eight points where the distances from the beacon are different, and an example of a graph of radio field strength values derived by the radio wave propagation model of the above equation (1). ing.

As shown in FIG. 12, the shorter the distance from the beacon, in other words, the closer to the beacon, the larger the deviation between the measured value and the radio field intensity value derived by the radio wave propagation model tends to be. That is, in the case shown in FIG. 12, the actual radio wave intensity cannot be appropriately approximated by one radio wave propagation model for the point near the beacon.

In general, when the radio wave propagation model is applied to a positioning device for positioning a user's position, the rate of change in radio wave intensity is large in the radio wave propagation model, and the distance from the beacon is within a certain range (near the beacon). Will be used. Therefore, the approximation accuracy of the radio wave propagation model in the vicinity of the beacon has a great influence on the positioning accuracy.

Therefore, in the present disclosure, the section near the beacon where the approximation accuracy of the radio wave propagation model is lowered is divided into a plurality of sections, and the model coefficients (n, C) derived using the measured values are used for each divided section. Apply the radio wave propagation model that was used. For example, when the measured value of the radio field intensity is obtained as shown in FIG. 1, first, the section where the rate of change of the radio field strength value is relatively large and the distance from the beacon is d0 to d2 (d0 <d2) and It is divided into sections where the rate of change of the radio field intensity value is relatively small and the distance from the beacon is d2 to d3 (d2 <d3). Further, the section whose distance from the beacon is d0 to d2 is divided into a plurality of sections (two sections d0 to d1 and sections d1 to d2). Then, for each section, the model coefficients (n, C) in the above equation (1) are derived to define a radio wave propagation model that approximates the radio wave propagation curve. Here, assuming that the spatial propagation coefficient of the sections d0 to d1 is n1, the spatial propagation coefficient of the sections d1 to d2 is n2, and the spatial propagation coefficient of the sections d2 to d3 is n3, the spatial propagation coefficient n1 is larger than the spatial propagation coefficient n2. It is large, and the relationship that the spatial propagation coefficient n2 is larger than the spatial propagation coefficient n3 (n1> n2> n3) is established. That is, the closer the section is to the beacon, the larger the value of the spatial propagation coefficient n. For example, the relationship of the following equation (2) holds.

n1 = n3 + 0.2
n2 = n3 + 0.04 ... (2)

By defining the radio wave propagation model of the above equation (1) with such spatial propagation coefficients n1, n2, and n3, as shown in FIG. 1, the radio wave intensity value derived by the radio wave propagation model for each section and the actual measurement The deviation from the value is suppressed, and the approximation accuracy by the radio wave propagation model is improved.

On the other hand, when the radio wave intensity values in all the sections are derived by the radio wave propagation model defined by the spatial propagation coefficient n3 applied in the sections d2 to d3, as shown in FIG. 2, in the vicinity of the beacon (sections d0 to d2), The discrepancy between the measured value and the radio field intensity value derived by the radio wave propagation model becomes large.

Therefore, in the present disclosure, as described above, the section according to the distance from the beacon is divided into a section in which the rate of change of the radio field intensity value is relatively large and a section in which the rate of change of the radio wave intensity value is relatively small. The section in which the rate of change of the radio wave intensity value is relatively small is divided into a plurality of sections, and the value of the spatial propagation coefficient n (n1 to n3 in FIG. 1) applied to the radio wave propagation model is switched for each section.

It is preferable that the section for switching the spatial propagation coefficient is shorter as it gets closer to the beacon. The closer it is to the beacon, the larger the rate of change of the radio wave intensity value (curvature of the radio wave propagation curve). Therefore, by shortening the section in which the spatial propagation coefficient is switched, the approximation accuracy of the radio wave propagation curve becomes higher.

As a method of partitioning to switch the spatial propagation coefficient, for example, the number of partitioning is changed according to the standard that minimizes the sum of squares of the approximation error with the radio wave propagation curve so that the error is minimized. , There is a method of automatically determining the number of interval divisions to the minimum number of divisions. Further, for example, as a method of partitioning an interval, a method of paying attention to a change in the curvature of the radio wave propagation curve and dividing at a point where the rate of change becomes equal to or higher than a threshold value can be mentioned. In the case of this method, the threshold value used when dividing into a section where the rate of change of the radio field intensity value is relatively large and a section where the rate of change of the radio wave intensity value is relatively small, and a section where the rate of change of the radio wave intensity value is relatively small. It is preferable that the threshold value used when dividing the section for switching the spatial propagation coefficient is different.

Next, the derivation of the electric field map using the radio wave propagation model of the present disclosure will be described. In the present embodiment, an electric field map that estimates the actual electric field in the desired region based on the measured value of the radio field intensity value in a desired region such as indoors according to the simulation conditions (hereinafter referred to as "actual electric field map"). Is derived. The electric field in a certain area changes depending on factors such as the structure (shape, material, etc.) of the building, etc. that constitutes the area, and the objects (walls, shelves, etc.) that shield the area. In the present embodiment, these factors in the region to be derived from the actual electric field map (hereinafter referred to as “derivation target region”) are set as simulation conditions.

In the present embodiment, first, the evaluation function f (n, C) represented by the following equation (3), which is composed of the measured value of the radio wave intensity of the beacon and the radio wave propagation model, is minimized by the quasi-Newton method or the like. The radio wave propagation model for each beacon is optimized by estimating the model coefficient (n, C) for each beacon provided in the derivation target region. In addition, "α" in the following equation (3) is a radio wave intensity value derived from the radio wave propagation model, and "β" is the radio wave intensity of a specific beacon at a specific point in the derivation target area. The "Σ" on the left side) represents the sum of all the measured points where the radio field strength was actually measured, and the "Σ" on the back (right side) represents the sum of the measured values of the radio field strength at a certain measured point.

f (n, C) = ΣΣ (α-β) ² ... (3)

An example of a method of optimizing the radio wave propagation model for each beacon will be described in detail with reference to FIG. FIG. 3 shows the measured radio field intensity values of the beacon B1 at four points (points A1 to A4) within the electric field range based on the radio field strength of the beacon B1 among the plurality of beacons provided in the derivation target area. The case is illustrated.

First, for point A1, the radio wave intensity value derived from the radio wave propagation model by applying the initial model coefficients (n, C) is set to α, and at point A1 in a state where it is not affected by the radio waves of other beacons. Let β be the measured value of the radio field intensity of beacon B1, and derive the square of (α-β). Similarly, the square of (α-β) is derived for points A2 to A4, and these are added to derive the evaluation function f (n, C). Next, the model coefficient (n, C) is changed from the initial value, and the square of (α-β) at points A1 to A4 is added in the same manner to derive the evaluation function f (n, C). Further, the derived evaluation functions f (n, C) are compared with each other, and if the evaluation function f (n, C) after the change of the model coefficient is smaller, the model coefficient (n, C) is further changed in the same direction. On the other hand, if the evaluation function f (n, C) after the change of the model coefficient is larger, the model coefficient (n, C) is changed in another direction. Then, in the same manner as described above, by repeating the derivation of the evaluation function f (n, C) and the comparison between the evaluation functions f (n, C), the model coefficient (n, C) at which the evaluation function f (n, C) is minimized ( n, C) is derived. The radio wave propagation model is optimized by applying the derived model coefficients (n, C).

In this embodiment, the radio wave propagation model is optimized as described above for all beacons in the derivation target region. Then, the actual electric field map is derived by synthesizing the electric fields based on the radio field intensity values derived from the optimized radio wave propagation models of all beacons.

When the evaluation function f (n, C) is minimized in order to optimize the radio wave propagation model as described above, the weighting according to the actual measurement point becomes heavier as the actual measurement point becomes more important in positioning. Weighting may be performed as follows. For example, when positioning indoors, that is, when the derivation target area is indoors, it is important to improve the approximation accuracy of the radio wave propagation model near the beacon. Therefore, the closer the distance from the beacon, the more important the actual measurement point for positioning. In this case, a weighting coefficient κ that becomes heavier (increased) as the distance is shorter is provided according to the distance from the beacon, and the difference between the derived radio wave intensity value α and the measured value β of the radio wave intensity for each term of the evaluation function. It is advisable to multiply the square of the weight by the weighting coefficient κ (κ × (α−β) ² ) to perform the weighting. By performing the weighting in this way, the approximation accuracy of the radio wave propagation model in the vicinity of the beacon is further improved as compared with the case where the least squares sum of the radio wave intensity value α and the measured value β of the radio wave intensity is derived evenly without weighting. Can be made to.

Next, the radio field intensity estimation device of the present embodiment, which is a device for deriving the above-mentioned actual electric field map, will be described.

FIG. 4 shows a configuration diagram of an example of the radio field intensity estimation device of the present embodiment. As shown in FIG. 4, the radio wave intensity estimation device 10 of the present embodiment includes a simulation condition setting unit 20, a derivation unit 22, an output unit 24, and an actually measured value DB (Data Base) 26. The radio field intensity estimation device of the present embodiment is specifically a computer program, and includes a ROM (Read Only Memory), a CPU (Central Processing Unit), a RAM (Random Access Memory), and the like that store the program. In the including computer, the CPU that executes the program functions as the simulation condition setting unit 20, the derivation unit 22, and the output unit 24 shown in FIG.

The activation unit 12 is a batch file, and from the simulation condition 2 including a plurality of setting files in which different simulation conditions are set, the setting file used for the simulation for creating the electric field map is specified, and the radio wave intensity is specified. It has a function of activating the estimation device 10.

The simulation condition 2 includes a plurality of setting files in which simulation conditions are set for each derivation target area.

The simulation condition setting unit 20 of the present embodiment has a function of reading a setting file corresponding to the derivation target area from the simulation condition 2 and setting the setting file to be available in the derivation unit 22. Therefore, the simulation condition setting unit 20 outputs the simulation conditions set according to the setting file.

Further, the simulation condition setting unit 20 of the present embodiment is used when optimizing the model coefficient (n, C) (minimizing the evaluation function f (n, C)) in the optimization unit 30, which will be described in detail later. It has a function to set the initial value of the model coefficient (n, C). Therefore, the simulation condition setting unit 20 outputs the model coefficients (n, C) used for deriving the optimization in response to the instruction of the optimization unit 30.

As described above, the derivation unit 22 of the present embodiment has a function of deriving the actual electric field map based on the radio wave propagation model and the measured value of the radio wave intensity value in the derivation target region. The data of the measured value of the radio wave intensity in the derivation target region is associated with each beacon and stored in the measured value DB 26.

As shown in FIG. 4, the derivation unit 22 of the present embodiment includes an optimization unit 30, an evaluation function derivation unit 32, an electric field estimation unit 34, and a radio wave propagation model unit 36. The radio wave propagation model unit 36 has a function of deriving a radio wave intensity value by the radio wave propagation model of the present disclosure described above. The model coefficient (n, C) optimized by the optimization unit 30, which will be described in detail later, is input to the radio wave propagation model unit 36 of the present embodiment. When the model coefficient (n, C) is input from the optimization unit 30, the radio wave propagation model unit 36 of the present embodiment receives the input model coefficient (n, C) in response to the instruction input from the electric field estimation unit 34. The radio wave intensity value is derived by the radio wave propagation model optimized by C), and the derived radio wave intensity value is output.

The electric field estimation unit 34 of the present embodiment has a function of setting a radio wave propagation model in the radio wave propagation model unit 36 and estimating the radio wave intensity value of the estimation target point by deriving the radio wave intensity value from the set radio wave propagation model. Have. Further, the electric field estimation unit 34 of the present embodiment is based on the radio wave intensity value input from the radio wave propagation model unit 36, the simulation conditions acquired from the simulation condition setting unit 20, and the actual measurement value acquired from the actual measurement value DB 26. It has a function of deriving and outputting the actual electric field map 6.

The evaluation function derivation unit 32 of the present embodiment is based on the actual measurement value acquired from the actual measurement value DB 26 and the radio wave intensity value derived by the radio wave propagation model unit 36 based on the instruction of the optimization unit 30. It has a function to derive and output the evaluation function f (n, C) by the equation 3). Therefore, the radio wave intensity value derived by the radio wave propagation model unit 36 is input to the evaluation function derivation unit 32 via the electric field estimation unit 34.

The optimization unit 30 of the present embodiment has a function of optimizing the radio wave propagation model of the radio wave propagation model unit 36 by deriving a model coefficient (n, C) that minimizes the evaluation function f (n, C). Have. Therefore, the optimization unit 30 of the present embodiment causes the evaluation function derivation unit 32 to derive the evaluation function f (n, C) by using the model coefficient (n, C) input from the simulation condition setting unit 20. Further, the simulation condition setting unit 20 is instructed to change the setting of the model coefficient (n, C), and the evaluation function is derived using the changed model coefficient (n, C) input from the simulation condition setting unit 20. The evaluation function f (n, C) is repeatedly derived by the unit 32, and as described above, the model coefficient (n, C) that minimizes (optimizes) the evaluation function f (n, C) is derived. In addition, the optimization unit 30 calculates the intermediate process of deriving the optimization, for example, the value of (α-β) ² in the above equation (3), the value of the evaluation function f (n, C), and the like. Output.

The intermediate progress output from the optimization unit 30 is input to the output unit 24 of the present embodiment, and the input intermediate progress is output to the outside as a progress record 4. Further, the actual electric field map 6 is input from the electric field estimation unit 34 to the output unit 24 of the present embodiment, and the input actual electric field map 6 is output. The output unit 24 is, for example, a monitor that displays the actual electric field map 6.

Next, the operation of the radio wave intensity estimation device 10 of the present embodiment will be described.

When activated by the activation unit 12, the radio wave intensity estimation device 10 first selects one beacon from a plurality of beacons provided in the derivation target area according to the simulation conditions, and an example is shown in FIG. Execute the propagation model derivation routine.

In step S10 shown in FIG. 5, the electric field estimation unit 34 acquires the measured value of the selected beacon from the measured value DB 26, and sets the radio wave arrival section of the selected beacon as the radio wave intensity value according to the rate of change of the radio wave intensity value. It is divided into a first section having a relatively large rate of change and a second section having a relatively small rate of change in radio field intensity value. For example, in the example shown in FIG. 1, the first section is divided into sections d0 to d2, and the second section is divided into sections d2 to d3. If the section used for positioning is predetermined according to the distance from the beacon, the section may be divided into a first section and a section outside the section as a second section.

In the next step S12, the electric field estimation unit 34 further divides the first section into a plurality of sections as described above. In the example shown in FIG. 1, the first section is divided into two sections, sections d0 to d1 and sections d1 to d2.

In the next step S14, the electric field estimation unit 34 derives the model coefficient (n, C) for each section to define a radio wave propagation model that approximates the radio wave propagation curve, and then performs a radio wave propagation model derivation routine. finish. In the example shown in FIG. 1, the spatial propagation coefficients n1, n2, and n3 are derived, and the derivation target region is defined by each of them.

The electric field estimation unit 34 sets the radio wave propagation model for each beacon in the radio wave propagation model unit 36 by executing the radio wave propagation model derivation routine for each of the plurality of beacons provided in the derivation target region. .. Needless to say, if the radio wave propagation model of each beacon is obtained in advance, the execution of the radio wave propagation model derivation routine can be omitted.

Next, the radio field intensity estimation device 10 executes the electric field map derivation routine shown in FIG. 6 as an example.

As shown in FIG. 6, in step S100, the radio wave intensity estimation device 10 is provided in the derivation target region by the optimization unit 30, the evaluation function derivation unit 32, the electric field estimation unit 34, and the radio wave propagation model unit 36. The radio wave propagation model is optimized according to the simulation conditions by minimizing the evaluation function f (n, C) for each beacon.

In the next step S102, the radio field intensity estimation device 10 synthesizes an electric field based on the radio wave intensity values derived from the optimized radio wave propagation models of all beacons as described above by the electric field estimation unit 34, thereby performing an actual electric field. Derivation of map 6. Specifically, the electric field estimation unit 34 uses an optimized radio wave propagation model represented by one equation as its coefficient, the spatial propagation coefficient, as the distance between the estimation target point for estimating the radio wave intensity and the beacon. The electric field due to each beacon is estimated by switching according to the situation. Then, the electric field estimation unit 34 derives the actual electric field map 6 by synthesizing the estimation results.

In the next step S104, the radio wave intensity estimation device 10 outputs the derived actual electric field map 6 by the output unit 24, and then ends the electric field map derivation routine. FIG. 7 shows an example of the display of the actual electric field map 6 derived in this way. FIG. 7 shows an example of an actual electric field map 6 represented by superimposing the arrangement of beacons and the electric field range of each beacon on the plan view of the inside of the building. Needless to say, the display method of the actual electric field map 6 is not limited to the one illustrated in FIG. 7. For example, as illustrated in FIG. 8, three-dimensional display may be performed with the intensity of radio waves as the vertical axis.

As described above, the radio wave intensity estimation device 10 of the present embodiment can present a region or the like where the radio wave of the beacon does not reach by deriving and displaying the actual electric field map. Therefore, according to the radio wave intensity estimation device 10 of the present embodiment, it is possible to easily improve the position where the beacon is arranged, and it is possible to improve the positioning accuracy for positioning the user's position by the beacon signal.

In the above, the radio field intensity estimation device 10 creates the actual electric field map 6 based on the simulation conditions that define the derivation target area and the data of the measured value of the radio wave intensity in the derivation target area stored in the measured value DB 26. Although the case of deriving is described in detail, the electric field map derived by the radio wave intensity estimation device 10 is not limited to the actual electric field map 6. For example, if the simulation conditions that define the derivation target area and the radio wave propagation model (or radio wave propagation curve) of the beacon are obtained, but the measured value data of the radio wave intensity in the derivation target area is not obtained, the radio wave intensity. The estimation device 10 may derive a theoretically obtained electric field map (hereinafter referred to as “theoretical electric field map”) based on the simulation conditions and the radio wave propagation model.

When deriving the theoretical electric field map, the radio wave intensity estimation device 10 may execute steps S102 and S104 of the electric field map deriving routine (see FIG. 6) described above based on the simulation conditions and the radio wave propagation model.

FIG. 9 shows an example of the display of the theoretical electric field map 8 derived by the radio field intensity estimation device 10. FIG. 9 shows an example of the theoretical electric field map 8 represented by a three-dimensional display with the intensity of radio waves as the vertical axis. In this way, as in the case of deriving the actual electric field map, when the theoretical electric field map is derived, it is possible to present a region or the like where the beacon radio wave does not reach. Therefore, according to the radio wave intensity estimation device 10 of the present embodiment, it is possible to easily improve the position where the beacon is arranged, and it is possible to improve the positioning accuracy for positioning the user's position by the beacon signal.

Next, a device for positioning provided with the radio wave intensity estimation device 10 of the present embodiment will be described. As described above, the radio field intensity estimation device 10 of the present embodiment is used as a positioning device for positioning the user's position. FIG. 10 shows a configuration diagram of an example of a device 100 for positioning provided with the radio field intensity estimation device 10 of the present embodiment. As shown in FIG. 10, the device 100 for positioning of the present embodiment includes a radio wave intensity estimation device 10, a communication I / F (Inter Face) 92, a positioning unit 94, and an output unit 96. The communication I / F 92 has a function of receiving a beacon signal from the beacon. The positioning unit 94 is based on the radio wave intensity of the beacon signal received by the communication I / F 92, the beacon ID that identifies the source beacon, and the actual electric field map or the theoretical electric field map derived by the radio wave intensity estimation device 10. It has a function of positioning the position of the device 100 itself for positioning. The output unit 96 has a function of outputting the positioning result of the positioning unit 94 as the position of the user.

As described above, the positioning device 100 of the present embodiment is a positioning device 100 that estimates the radio wave intensity at a desired position of the radio wave transmitted from the beacon, which is an example of the radio wave transmitting device. Therefore, in the section according to the distance from the beacon, the first section in which the rate of change of the radio wave intensity value with respect to the change in distance is less than the threshold value and the section in which the rate of change of the radio wave intensity value is equal to or more than the threshold value are higher than the first section. It is divided into a second section closer to the beacon, and the second section is further divided into a plurality of sections, and the value of the spatial propagation coefficient n whose value becomes larger as the section closer to the beacon becomes larger for each divided section is switched. The electric field estimation unit 34 for estimating the radio wave intensity of the estimation target point by the radio wave propagation model represented by one equation based on the distance between the beacon and the estimation target point for estimating the radio wave intensity and the spatial propagation coefficient n is provided. .. That is, the device 100 for positioning of the present embodiment includes the radio field intensity estimation device 10 of the present embodiment.

Therefore, according to the device 100 for positioning of the present embodiment, the intensity of radio waves can be accurately estimated regardless of the distance from the beacon which is the source of radio waves.

The radio field intensity estimation device 10 of the present embodiment can be mounted as in the example shown in FIG. 11, for example. An example of mounting the radio wave intensity estimation device 10 shown in FIG. 11 includes a survey data conversion unit 50, a simulation condition setting file 58, a project file 60, a GUI (Graphical User Interface) unit 62, and a derivation unit 22. Be prepared.

As shown in FIG. 11, the survey data conversion unit 50 includes an actual measurement value DB 26, a survey application 52, a data extraction / shaping unit 54, and an actual measurement data preprocessing unit 56. The survey application is an application that performs a so-called site survey in the derivation target area, and the data of the measured value of the radio wave intensity of the beacon measured by the survey application 52 is stored in the measured value DB 26. The measured value data stored in the measured value DB 26 is prepared for use by the derivation unit 22 by the data extraction / shaping unit 54 and the actual measurement data preprocessing unit 56, and is converted into a project file (project file 60). Further, the simulation conditions that define the derivation target area are stored in the simulation condition setting file 58, and are converted into a project file (project file 60).

Further, as shown in FIG. 11, the derivation unit 22 includes an actual electric field derivation unit 70, a theoretical electric field derivation unit 72, a radio wave propagation model 76, and an evaluation function 78. When deriving the actual electric field map, the actual electric field deriving unit 70 of the deriving unit 22 reads the project file 60, derives the actual electric field map as described above using the radio wave propagation model 76 and the evaluation function 78, and derives the project file 60. Output to. When deriving the theoretical electric field map, the theoretical electric field deriving unit 72 of the deriving unit 22 reads the project file 60, derives the theoretical electric field map as described above using the radio wave propagation model 76, and outputs it to the project file 60. To do. The actual electric field map and the theoretical electric field map output to the project file 60 can be viewed by a user or the like by the GUI unit 62.

It should be noted that this embodiment is an example, and the specific configuration is not limited to this embodiment, but includes a design and the like within a range that does not deviate from the gist of the present invention, and can be changed depending on the situation. Needless to say.

For example, in the present embodiment, when the electric field estimation unit 34 optimizes the radio wave propagation model (minimization of the evaluation function f (n, C)), the embodiment using the measured values of the radio wave intensities at all the measured points. As described above, the present invention is not limited to this form, and the measured values of the radio field intensity for at least two or more actual measurement points may be used.

Further, for example, in the present embodiment, the embodiment using the radio wave propagation model represented by the above equation (1) has been described, but the radio wave propagation model is not limited to this embodiment, and at least, “K” in the above equation (1). Any one expression may be used, which is represented by an expression including −n × log ₁₀ d ”. For example, the radio wave propagation model may be an equation that does not include the model coefficient C on the right side of the equation (1).

10 Radio field strength estimation device 30 Optimization unit 34 Electric field estimation unit 94 Positioning unit 100 Device for positioning

Claims (8)

It is a device for positioning that estimates the radio wave strength at a desired position of the radio wave transmitted from the radio wave transmitter.
The section corresponding to the distance from the radio wave transmitting device includes the first section in which the rate of change of the radio wave intensity value with respect to the change in the distance is less than the threshold value and the section in which the rate of change of the radio wave intensity value is equal to or more than the threshold value. The section is divided into a second section closer to the radio wave transmitting device than the section of the above, and the second section is further divided into a plurality of sections, and the value is larger in each divided section as the section closer to the radio wave transmitting device. The estimation is performed by a radio wave propagation model represented by one equation based on the distance between the radio wave transmitting device and the estimation target point for estimating the radio wave intensity and the space propagation coefficient by switching the value of the space propagation coefficient. Equipped with an electric field estimation unit that estimates the radio field strength at the target point,
Equipment for positioning. A positioning unit that performs positioning of the estimation target point based on the radio field intensity of the estimation target point estimated by the electric field estimation unit and the measured value of the radio wave intensity of the estimation target point is further provided.
The device for positioning according to claim 1. The second section is divided into shorter sections as it is closer to the radio wave transmitting device.
The device for positioning according to claim 1 or 2. In the radio wave propagation model, when the maximum radio wave output of the radio wave transmitted by the radio wave transmitting device is K, the distance between the radio wave transmitting device and the estimated target point is d, and the spatial propagation coefficient is n, the radio wave intensity value is used. It is represented by an equation that includes at least the right side of equation (1) below, which derives a certain RSSI (Received Signal Strength Indicator).
RSSI = Kn × log ₁₀ d ・ ・ ・ (1)
The device for positioning according to any one of claims 1 to 3. Further provided with an optimization unit that optimizes the radio wave propagation model by optimizing the spatial propagation coefficient using the measured values obtained by actually measuring the radio wave intensity of the radio wave transmitting device at each of the measured points whose positions are known. ,
The device for positioning according to any one of claims 1 to 4. The optimization unit minimizes an optimization function that represents the sum of the differences between the measured values of the radio field intensity for at least two or more actually measured points where the radio wave intensity is actually measured and the radio field intensity values derived from the radio wave propagation model. As described above, the radio wave propagation model is optimized by deriving the spatial propagation coefficient related to the distance between the measured point and the radio wave transmitting device.
The device for positioning according to claim 5. The optimization unit further optimizes the radio wave propagation model by performing greater weighting as the distance between the radio wave transmitting device and the actually measured point becomes closer.
The device for positioning according to claim 6. A program for causing a computer to function as each part of the device for positioning according to any one of claims 1 to 7.